Connect from Cloud Run

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This page contains information and examples for connecting to a Cloud SQL instance from a service running in Cloud Run.

For step-by-step instructions on running a Cloud Run sample web application connected to Cloud SQL, see the quickstart for connecting from Cloud Run.

Cloud SQL is a fully-managed database service that helps you set up, maintain, manage, and administer your relational databases in the cloud.

Cloud Run is a managed compute platform that lets you run containers directly on top of Google Cloud infrastructure.

Set up a Cloud SQL instance

  1. Enable the Cloud SQL Admin API in the project you are connecting from, if you haven't already done so:

    Enable the API

  2. Create a Cloud SQL for PostgreSQL instance.

    By default, Cloud SQL assigns a public IP address to a new instance. You also have the option to assign a private IP address. For more information about the connectivity options for both, see the Connecting Overview page.

Configure Cloud Run

The steps to configure Cloud Run depend on the type of IP address you assigned to your Cloud SQL instance. If you route all egress traffic through the VPC connector, you must use a Private IP.

Public IP (default)

  • Make sure that the instance created earlier has a public IP address. You can verify this on the Overview page for your instance in the Google Cloud console. If you need to add one, see the Configuring public IP page for instructions.
  • Get the INSTANCE_CONNECTION_NAME for your instance. This can be found on the Overview page for your instance in the Google Cloud console. or by running the following command: gcloud sql instances describe INSTANCE_NAME.
  • Configure the service account for your service. Make sure that the service account has the appropriate Cloud SQL roles and permissions to connect to Cloud SQL.
      The service account for your service needs one of the following IAM roles:
      • Cloud SQL Client (preferred)
      • Cloud SQL Admin
      Or, you can manually assign the following IAM permissions:
      • cloudsql.instances.connect
      • cloudsql.instances.get

    If the authorizing service account belongs to a different project than the Cloud SQL instance, the Cloud SQL Admin API and IAM permissions will need to be added for both projects.

Like any configuration change, setting a new configuration for the Cloud SQL connection leads to the creation of a new Cloud Run revision. Subsequent revisions will also automatically get this Cloud SQL connection unless you make explicit updates to change it.

Console

  1. Go to Cloud Run

  2. Configure the service:

    • If you are adding a Cloud SQL connection to a new service:
      • You need to have your service containerized and uploaded to the Container Registry. If you don't already have one, see these instructions about building and deploying a container image.
      • Click Create service.

    • If you are adding Cloud SQL connections to an existing service:
      • Click on the service name.
      • Click on the Connections tab.
      • Click Deploy.
  3. Enable connecting to a Cloud SQL instance:
    • Click Container, Variables & Secrets, Connections, Security .
    • Click on the Connections tab.

    Add Cloud SQL connection

    • If you are adding a connection to a Cloud SQL instance in your project, select the desired Cloud SQL instance from the dropdown menu.
    • If you are using a Cloud SQL instance from another project, select custom connection string in the dropdown and then enter the full instance connection name in the format PROJECT-ID:REGION:INSTANCE-ID.
    • If you are deleting a connection, hover your cursor to the right of the connection to display the Trash icon, and click it.
  4. Click Create or Deploy.

Command line

Before using any of the commands below, make the following replacements:

  • IMAGE with the image you are deploying
  • SERVICE_NAME with the name of your Cloud Run service
  • INSTANCE_CONNECTION_NAME with the instance connection name of your Cloud SQL instance, or a comma delimited list of connection names.

    If you are deploying a new container, use the following command:

    gcloud run deploy \
    --image=IMAGE \
    --add-cloudsql-instances=INSTANCE_CONNECTION_NAME
                
    If you are updating an existing service, use the following command:
    gcloud run services update SERVICE_NAME \
    --add-cloudsql-instances=INSTANCE_CONNECTION_NAME
                

Terraform

The following highlighted lines create a base Cloud Run container.

resource "google_cloud_run_service" "default" {
  name     = "cloudrun-service"
  location = "us-central1"

  template {
    spec {
      containers {
        image = "us-docker.pkg.dev/cloudrun/container/hello:latest" # Image to deploy
        # Sets a environment variable for instance connection name
        env {
          name  = "INSTANCE_CONNECTION_NAME"
          value = google_sql_database_instance.mysql_instance.connection_name
        }
        # Sets a secret environment variable for database user secret
        env {
          name = "DB_USER"
          value_from {
            secret_key_ref {
              name = google_secret_manager_secret.dbuser.secret_id # secret name
              key  = "latest"                                      # secret version number or 'latest'
            }
          }
        }
        # Sets a secret environment variable for database password secret
        env {
          name = "DB_PASS"
          value_from {
            secret_key_ref {
              name = google_secret_manager_secret.dbpass.secret_id # secret name
              key  = "latest"                                      # secret version number or 'latest'
            }
          }
        }
        # Sets a secret environment variable for database name secret
        env {
          name = "DB_NAME"
          value_from {
            secret_key_ref {
              name = google_secret_manager_secret.dbname.secret_id # secret name
              key  = "latest"                                      # secret version number or 'latest'
            }
          }
        }
      }
    }

    metadata {
      annotations = {
        "run.googleapis.com/client-name" = "terraform"
      }
    }
  }

  autogenerate_revision_name = true
  depends_on                 = [google_project_service.secretmanager_api, google_project_service.cloudrun_api, google_project_service.sqladmin_api]
}

  1. Create a container similar to that of the above example. Apply the changes by entering terraform apply.
  2. Connect the SQL instance to the Cloud Run resource by adding the following under metadata.annotations.
    metadata {
       annotations = {
          "autoscaling.knative.dev/maxScale" = "1000"
          "run.googleapis.com/cloudsql-instances" = google_sql_database_instance.mysql_instance.connection_name
          ...
       }
    }
  3. In order for the Cloud SQL connection to be applied in Cloud Run resource, a container revision must take place. Update the Cloud Run resource `image` property with a new Cloud Build revision. Apply the changes by entering terraform apply.
  4. Verify the changes by checking the Cloud Run service, clicking **Revisions** tab, and **Connections** tab.

Private IP

A Serverless VPC Access connector handles communication to your VPC network. To connect directly with private IP, you need to:

  1. Make sure that the Cloud SQL instance created above has a private IP address. If you need to add one, see the Configuring private IP page for instructions.
  2. Create a Serverless VPC Access connector in the same VPC network as your Cloud SQL instance.
  3. Unless you're using Shared VPC, a connector must be in the same project and region as the resource that uses it, but the connector can send traffic to resources in different regions.

    Serverless VPC Access supports communication to VPC networks connected via Cloud VPN and VPC Network Peering.

    Serverless VPC Access does not support legacy networks.

  4. Configure Cloud Run to use the connector.
  5. Connect using your instance's private IP and port 5432.

Connect to Cloud SQL

After you configure Cloud Run, you can connect to your Cloud SQL instance.

Public IP (default)

For public IP paths, Cloud Run provides encryption and connects using the Cloud SQL Auth proxy in two ways:

Use Secret Manager

Google recommends that you use Secret Manager to store sensitive information such as SQL credentials. You can pass secrets as environment variables or mount as a volume with Cloud Run.

After creating a secret in Secret Manager, update an existing service, with the following command:

Command line

        gcloud run services update SERVICE_NAME \
        --add-cloudsql-instances=INSTANCE_CONNECTION_NAME
        --update-env-vars=INSTANCE_CONNECTION_NAME=INSTANCE_CONNECTION_NAME_SECRET \
        --update-secrets=DB_USER=DB_USER_SECRET:latest \
        --update-secrets=DB_PASS=DB_PASS_SECRET:latest \
        --update-secrets=DB_NAME=DB_NAME_SECRET:latest
      

Terraform

The following creates secret resources to securely hold the database user, password, and name values using google_secret_manager_secret and google_secret_manager_secret_version. Note that you must update the project compute service account to have access to each secret.


# Create dbuser secret
resource "google_secret_manager_secret" "dbuser" {
  secret_id = "dbusersecret"
  replication {
    automatic = true
  }
  depends_on = [google_project_service.secretmanager_api]
}

# Attaches secret data for dbuser secret
resource "google_secret_manager_secret_version" "dbuser_data" {
  secret      = google_secret_manager_secret.dbuser.id
  secret_data = "secret-data" # Stores secret as a plain txt in state
}

# Update service account for dbuser secret
resource "google_secret_manager_secret_iam_member" "secretaccess_compute_dbuser" {
  secret_id = google_secret_manager_secret.dbuser.id
  role      = "roles/secretmanager.secretAccessor"
  member    = "serviceAccount:${data.google_project.project.number}-compute@developer.gserviceaccount.com" # Project's compute service account
}


# Create dbpass secret
resource "google_secret_manager_secret" "dbpass" {
  secret_id = "dbpasssecret"
  replication {
    automatic = true
  }
  depends_on = [google_project_service.secretmanager_api]
}

# Attaches secret data for dbpass secret
resource "google_secret_manager_secret_version" "dbpass_data" {
  secret      = google_secret_manager_secret.dbpass.id
  secret_data = "secret-data" # Stores secret as a plain txt in state
}

# Update service account for dbpass secret
resource "google_secret_manager_secret_iam_member" "secretaccess_compute_dbpass" {
  secret_id = google_secret_manager_secret.dbpass.id
  role      = "roles/secretmanager.secretAccessor"
  member    = "serviceAccount:${data.google_project.project.number}-compute@developer.gserviceaccount.com" # Project's compute service account
}


# Create dbname secret
resource "google_secret_manager_secret" "dbname" {
  secret_id = "dbnamesecret"
  replication {
    automatic = true
  }
  depends_on = [google_project_service.secretmanager_api]
}

# Attaches secret data for dbname secret
resource "google_secret_manager_secret_version" "dbname_data" {
  secret      = google_secret_manager_secret.dbname.id
  secret_data = "secret-data" # Stores secret as a plain txt in state
}

# Update service account for dbname secret
resource "google_secret_manager_secret_iam_member" "secretaccess_compute_dbname" {
  secret_id = google_secret_manager_secret.dbname.id
  role      = "roles/secretmanager.secretAccessor"
  member    = "serviceAccount:${data.google_project.project.number}-compute@developer.gserviceaccount.com" # Project's compute service account
}

Update the main Cloud Run resource to include the new secrets.

resource "google_cloud_run_service" "default" {
  name     = "cloudrun-service"
  location = "us-central1"

  template {
    spec {
      containers {
        image = "us-docker.pkg.dev/cloudrun/container/hello:latest" # Image to deploy
        # Sets a environment variable for instance connection name
        env {
          name  = "INSTANCE_CONNECTION_NAME"
          value = google_sql_database_instance.mysql_instance.connection_name
        }
        # Sets a secret environment variable for database user secret
        env {
          name = "DB_USER"
          value_from {
            secret_key_ref {
              name = google_secret_manager_secret.dbuser.secret_id # secret name
              key  = "latest"                                      # secret version number or 'latest'
            }
          }
        }
        # Sets a secret environment variable for database password secret
        env {
          name = "DB_PASS"
          value_from {
            secret_key_ref {
              name = google_secret_manager_secret.dbpass.secret_id # secret name
              key  = "latest"                                      # secret version number or 'latest'
            }
          }
        }
        # Sets a secret environment variable for database name secret
        env {
          name = "DB_NAME"
          value_from {
            secret_key_ref {
              name = google_secret_manager_secret.dbname.secret_id # secret name
              key  = "latest"                                      # secret version number or 'latest'
            }
          }
        }
      }
    }

    metadata {
      annotations = {
        "run.googleapis.com/client-name" = "terraform"
      }
    }
  }

  autogenerate_revision_name = true
  depends_on                 = [google_project_service.secretmanager_api, google_project_service.cloudrun_api, google_project_service.sqladmin_api]
}

Apply the changes by entering terraform apply.

The example command uses the secret version, latest; however, Google recommends pinning the secret to a specific version, SECRET_NAME:v1.

Private IP

For private IP paths, your application will connect directly to your instance through Serverless VPC Access. This method uses TCP to connect directly to the Cloud SQL instance without using the Cloud SQL Auth proxy.

Connect with TCP

Connect directly using the private IP address and port 5432 for your instance.

Python

To see this snippet in the context of a web application, view the README on GitHub.

import os
import ssl

import sqlalchemy


def connect_tcp_socket() -> sqlalchemy.engine.base.Engine:
    """ Initializes a TCP connection pool for a Cloud SQL instance of Postgres. """
    # Note: Saving credentials in environment variables is convenient, but not
    # secure - consider a more secure solution such as
    # Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
    # keep secrets safe.
    db_host = os.environ["INSTANCE_HOST"]  # e.g. '127.0.0.1' ('172.17.0.1' if deployed to GAE Flex)
    db_user = os.environ["DB_USER"]  # e.g. 'my-db-user'
    db_pass = os.environ["DB_PASS"]  # e.g. 'my-db-password'
    db_name = os.environ["DB_NAME"]  # e.g. 'my-database'
    db_port = os.environ["DB_PORT"]  # e.g. 5432

    pool = sqlalchemy.create_engine(
        # Equivalent URL:
        # postgresql+pg8000://<db_user>:<db_pass>@<db_host>:<db_port>/<db_name>
        sqlalchemy.engine.url.URL.create(
            drivername="postgresql+pg8000",
            username=db_user,
            password=db_pass,
            host=db_host,
            port=db_port,
            database=db_name,
        ),
        # ...
    )
    return pool

Java

To see this snippet in the context of a web application, view the README on GitHub.

Note:

  • CLOUD_SQL_CONNECTION_NAME should be represented as <MY-PROJECT>:<INSTANCE-REGION>:<INSTANCE-NAME>
  • Using the argument ipTypes=PRIVATE will force the SocketFactory to connect with an instance's associated private IP
  • See the JDBC socket factory version requirements for the pom.xml file here .


import com.zaxxer.hikari.HikariConfig;
import com.zaxxer.hikari.HikariDataSource;
import javax.sql.DataSource;

public class TcpConnectionPoolFactory extends ConnectionPoolFactory {

  // Note: Saving credentials in environment variables is convenient, but not
  // secure - consider a more secure solution such as
  // Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
  // keep secrets safe.
  private static final String DB_USER = System.getenv("DB_USER");
  private static final String DB_PASS = System.getenv("DB_PASS");
  private static final String DB_NAME = System.getenv("DB_NAME");

  private static final String INSTANCE_HOST = System.getenv("INSTANCE_HOST");
  private static final String DB_PORT = System.getenv("DB_PORT");


  public static DataSource createConnectionPool() {
    // The configuration object specifies behaviors for the connection pool.
    HikariConfig config = new HikariConfig();

    // The following URL is equivalent to setting the config options below:
    // jdbc:postgresql://<INSTANCE_HOST>:<DB_PORT>/<DB_NAME>?user=<DB_USER>&password=<DB_PASS>
    // See the link below for more info on building a JDBC URL for the Cloud SQL JDBC Socket Factory
    // https://github.com/GoogleCloudPlatform/cloud-sql-jdbc-socket-factory#creating-the-jdbc-url

    // Configure which instance and what database user to connect with.
    config.setJdbcUrl(String.format("jdbc:postgresql://%s:%s/%s", INSTANCE_HOST, DB_PORT, DB_NAME));
    config.setUsername(DB_USER); // e.g. "root", "postgres"
    config.setPassword(DB_PASS); // e.g. "my-password"


    // ... Specify additional connection properties here.
    // ...

    // Initialize the connection pool using the configuration object.
    return new HikariDataSource(config);
  }
}

Node.js

To see this snippet in the context of a web application, view the README on GitHub.

const Knex = require('knex');
const fs = require('fs');

// createTcpPool initializes a TCP connection pool for a Cloud SQL
// instance of Postgres.
const createTcpPool = async config => {
  // Note: Saving credentials in environment variables is convenient, but not
  // secure - consider a more secure solution such as
  // Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
  // keep secrets safe.
  const dbConfig = {
    client: 'pg',
    connection: {
      host: process.env.INSTANCE_HOST, // e.g. '127.0.0.1'
      port: process.env.DB_PORT, // e.g. '5432'
      user: process.env.DB_USER, // e.g. 'my-user'
      password: process.env.DB_PASS, // e.g. 'my-user-password'
      database: process.env.DB_NAME, // e.g. 'my-database'
    },
    // ... Specify additional properties here.
    ...config,
  };
  // Establish a connection to the database.
  return Knex(dbConfig);
};

Go

To see this snippet in the context of a web application, view the README on GitHub.

package cloudsql

import (
	"database/sql"
	"fmt"
	"log"
	"os"

	// Note: If connecting using the App Engine Flex Go runtime, use
	// "github.com/jackc/pgx/stdlib" instead, since v4 requires
	// Go modules which are not supported by App Engine Flex.
	_ "github.com/jackc/pgx/v4/stdlib"
)

// connectTCPSocket initializes a TCP connection pool for a Cloud SQL
// instance of Postgres.
func connectTCPSocket() (*sql.DB, error) {
	mustGetenv := func(k string) string {
		v := os.Getenv(k)
		if v == "" {
			log.Fatalf("Warning: %s environment variable not set.", k)
		}
		return v
	}
	// Note: Saving credentials in environment variables is convenient, but not
	// secure - consider a more secure solution such as
	// Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
	// keep secrets safe.
	var (
		dbUser    = mustGetenv("DB_USER")       // e.g. 'my-db-user'
		dbPwd     = mustGetenv("DB_PASS")       // e.g. 'my-db-password'
		dbTCPHost = mustGetenv("INSTANCE_HOST") // e.g. '127.0.0.1' ('172.17.0.1' if deployed to GAE Flex)
		dbPort    = mustGetenv("DB_PORT")       // e.g. '5432'
		dbName    = mustGetenv("DB_NAME")       // e.g. 'my-database'
	)

	dbURI := fmt.Sprintf("host=%s user=%s password=%s port=%s database=%s",
		dbTCPHost, dbUser, dbPwd, dbPort, dbName)


	// dbPool is the pool of database connections.
	dbPool, err := sql.Open("pgx", dbURI)
	if err != nil {
		return nil, fmt.Errorf("sql.Open: %v", err)
	}

	// ...

	return dbPool, nil
}

C#

To see this snippet in the context of a web application, view the README on GitHub.

using Npgsql;
using System;

namespace CloudSql
{
    public class PostgreSqlTcp
    {
        public static NpgsqlConnectionStringBuilder NewPostgreSqlTCPConnectionString()
        {
            // Equivalent connection string:
            // "Uid=<DB_USER>;Pwd=<DB_PASS>;Host=<INSTANCE_HOST>;Database=<DB_NAME>;"
            var connectionString = new NpgsqlConnectionStringBuilder()
            {
                // Note: Saving credentials in environment variables is convenient, but not
                // secure - consider a more secure solution such as
                // Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
                // keep secrets safe.
                Host = Environment.GetEnvironmentVariable("INSTANCE_HOST"),     // e.g. '127.0.0.1'
                // Set Host to 'cloudsql' when deploying to App Engine Flexible environment
                Username = Environment.GetEnvironmentVariable("DB_USER"), // e.g. 'my-db-user'
                Password = Environment.GetEnvironmentVariable("DB_PASS"), // e.g. 'my-db-password'
                Database = Environment.GetEnvironmentVariable("DB_NAME"), // e.g. 'my-database'

                // The Cloud SQL proxy provides encryption between the proxy and instance.
                SslMode = SslMode.Disable,
            };
            connectionString.Pooling = true;
            // Specify additional properties here.
            return connectionString;
        }
    }
}

Ruby

To see this snippet in the context of a web application, view the README on GitHub.

tcp: &tcp
  adapter: postgresql
  # Configure additional properties here.
  # Note: Saving credentials in environment variables is convenient, but not
  # secure - consider a more secure solution such as
  # Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
  # keep secrets safe.
  username: <%= ENV["DB_USER"] %>  # e.g. "my-database-user"
  password: <%= ENV["DB_PASS"] %> # e.g. "my-database-password"
  database: <%= ENV.fetch("DB_NAME") { "vote_development" } %>
  host: <%= ENV.fetch("INSTANCE_HOST") { "127.0.0.1" }%> # '172.17.0.1' if deployed to GAE Flex
  port: <%= ENV.fetch("DB_PORT") { 5432 }%>

PHP

To see this snippet in the context of a web application, view the README on GitHub.

namespace Google\Cloud\Samples\CloudSQL\Postgres;

use PDO;
use PDOException;
use RuntimeException;
use TypeError;

class DatabaseTcp
{
    public static function initTcpDatabaseConnection(): PDO
    {
        try {
            // Note: Saving credentials in environment variables is convenient, but not
            // secure - consider a more secure solution such as
            // Cloud Secret Manager (https://cloud.google.com/secret-manager) to help
            // keep secrets safe.
            $username = getenv('DB_USER'); // e.g. 'your_db_user'
            $password = getenv('DB_PASS'); // e.g. 'your_db_password'
            $dbName = getenv('DB_NAME'); // e.g. 'your_db_name'
            $instanceHost = getenv('INSTANCE_HOST'); // e.g. '127.0.0.1' ('172.17.0.1' for GAE Flex)

            // Connect using TCP
            $dsn = sprintf('pgsql:dbname=%s;host=%s', $dbName, $instanceHost);

            // Connect to the database
            $conn = new PDO(
                $dsn,
                $username,
                $password,
                # ...
            );
        } catch (TypeError $e) {
            throw new RuntimeException(
                sprintf(
                    'Invalid or missing configuration! Make sure you have set ' .
                        '$username, $password, $dbName, and $instanceHost (for TCP mode). ' .
                        'The PHP error was %s',
                    $e->getMessage()
                ),
                $e->getCode(),
                $e
            );
        } catch (PDOException $e) {
            throw new RuntimeException(
                sprintf(
                    'Could not connect to the Cloud SQL Database. Check that ' .
                        'your username and password are correct, that the Cloud SQL ' .
                        'proxy is running, and that the database exists and is ready ' .
                        'for use. For more assistance, refer to %s. The PDO error was %s',
                    'https://cloud.google.com/sql/docs/postgres/connect-external-app',
                    $e->getMessage()
                ),
                $e->getCode(),
                $e
            );
        }

        return $conn;
    }
}

Best practices and other information

You can use the Cloud SQL Auth proxy when testing your application locally. See the quickstart for using the Cloud SQL Auth proxy for detailed instructions.

You can also test using the Cloud SQL Proxy via a docker container.

Connection Pools

Connections to underlying databases may be dropped, either by the database server itself, or by the platform infrastructure. We recommend using a client library that supports connection pools that automatically reconnect broken client connections. For more detailed examples on how to use connection pools, see the Managing database connections page.

Connection Limits

Both the MySQL and PostgreSQL editions of Cloud SQL impose a maximum limit on concurrent connections, and these limits may vary depending on the database engine chosen (see the Cloud SQL Quotas and Limits page).

Cloud Run services are limited to 100 connections to a Cloud SQL database. This limit applies per service instance. This means that each instance of the Cloud Run service can have 100 connections to the database, and as it scales the total number of connections per deployment can grow.

You can limit the maximum number of connections used per instance by using a connection pool. For more detailed examples on how to limit the number of connections, see the Managing database connections page.

API Quota Limits

Cloud Run provides a mechanism that connects using the Cloud SQL Auth proxy, which uses the Cloud SQL Admin API. API quota limits apply to the Cloud SQL Auth proxy. The Cloud SQL Admin API quota used is approximately two times the number of Cloud SQL instances configured by the number of Cloud Run instances of a particular service deployed at any one time. You can cap or increase the number of Cloud Run instances to modify the expected API quota consumed.

Next steps